Factor Analysis and Variance Partitioning in Intelligence Test Research: Clarifying Misconceptions

2020 ◽  
pp. 073428292096195 ◽  
Author(s):  
Stefan C. Dombrowski ◽  
Ryan J. McGill ◽  
Gary L. Canivez ◽  
Marley W. Watkins ◽  
A. Alexander Beaujean
Keyword(s):  
Factor Analysis ◽  
Online Publication ◽  
Variance Partitioning ◽  
Intelligence Test ◽  
Psychoeducational Assessment ◽  
Cognitive Measures ◽  
Factor Analytic

This article addresses conceptual and methodological shortcomings regarding conducting and interpreting intelligence test factor analytic research that appeared in the Decker, S. L., Bridges, R. M., Luedke, J. C., & Eason, M. J. (2020). Dimensional evaluation of cognitive measures: Methodological confounds and theoretical concerns. Journal of Psychoeducational Assessment. Advance online publication article.

Relation between Number of Subjects and Homogeneity of the Scale in Factor Analytic Studies

1997 ◽  
Vol 85 (3_suppl) ◽  
pp. 1168-1170
Author(s):  
S. M. S. Ahmed ◽  
André Michon
Keyword(s):  
Factor Analysis ◽  
Factor Analytic ◽  
Variance Explained

This paper describes a factor analysis of the responses of 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, or 160 subjects. The result shows that homogeneous scales need fewer subjects than heterogeneous scales for stable results in terms of the number of extracted factors and percentage of variance explained.

Factor-Analytic Study of the Maitland Graves Design Judgment Test

1967 ◽  
Vol 24 (1) ◽  
pp. 73-74 ◽  
Author(s):  
H. J. Eysenck
Keyword(s):  
Factor Analysis ◽  
Analytic Study ◽  
Young Males ◽  
Factor Analytic ◽  
Factor Analytic Study ◽  
Five Factors

A factor-analysis was carried out of the 90 items of the Maitland Graves Design Judgment Test based on responses from 172 young males. Five factors were found, of which only four could be interpreted.

scholarly journals Prestasiebeoordeling: 'n Faktoranalitiese geldigheidstudie

1988 ◽  
Vol 14 (2) ◽  
Author(s):  
W. P. Smith ◽  
A. L. Barnard ◽  
H. S. Steyn
Keyword(s):  
Factor Analysis ◽  
Performance Appraisal ◽  
Validation Study ◽  
Work Ability ◽  
Measuring Instrument ◽  
Appraisal System ◽  
General Validity ◽  
Factor Analytic ◽  
Management Ability ◽  
Performance Appraisal System

Performance appraisal: a factor analytic validation study. The purpose of the study was to establish the validity of a general performance appraisal system through the application of factor analysis. It is found that the performance appraisal system to some extent do dispose a general validity, and that the three constructs involved (management ability, work ability, and ability to adapt) can be evaluated satisfactorily by the measuring instrument mentioned. Opsomming Die doel van die studie was die geldigheidsbepaling van 'n algemene prestasiebeoordelingstelsel deur die toepassing van faktorontleding. Daar is bevind dat die prestasiebeoordelingstelsel wel oor 'n aanvaarbare mate van algemene geldigheid beskik, veral sover dit konstrukgeldigheid aangaan, en dat die drie konstrukte, bestuurs-, werks- en aanpassingsvermoe, wel tot 'n bevredigende mate deur die betrokke meetinstrument geevalueer kan word.

Dimensional Analyses of Taxonic Data

2007 ◽  
Vol 101 (2) ◽  
pp. 617-635 ◽  
Author(s):  
William M. Grove
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Data Structures ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Mixed Population ◽  
Single Population ◽  
Factor Analytic ◽  
Mixed Populations

Principal component analysis (PCA) and common factor analysis are often used to model latent data structures. Typically, such analyses assume a single population whose correlation or covariance matrix is modelled. However, data may sometimes be unwittingly sampled from mixed populations containing a taxon (nonarbitrary subpopulation) and its complement class. One derives relations between values of PCA parameters within subpopulations and their values in the mixed population. These results are then extended to factor analysis in mixed populations. As relationships between subpopulation and mixed-population principal components and factors sensitively depend on within-subpopulation structures and between-subpopulation differences, naive interpretation of PCA or factor analytic findings can potentially mislead. Several analyses, better suited to the dimensional analysis of admixture data structures, are presented and compared.

Confirmation of Objective Test Factors and Assessment of Their Relation to Questionnaire Factors: A Factor Analysis of 113 Rating, Questionnaire and Objective Test Measurements of Personality

1958 ◽  
Vol 104 (436) ◽  
pp. 608-624 ◽  
Author(s):  
Ivan H. Scheier ◽  
Raymond B. Cattell
Keyword(s):  
Factor Analysis ◽  
Objective Test ◽  
Personality Factors ◽  
Single Factor ◽  
Basic Strategy ◽  
Self Rating ◽  
Personality Research ◽  
Factor Analytic ◽  
Objective Tests

Cattell's basic strategy in personality research has been first to establish personality factors for each of three major types of measurement, rating (Life-Record), questionnaire (Self-Rating), and objective tests, then to compare factors from one realm with factors from another (7). A factor in any one realm is established in the first place by being replicated. As Cattell says (4, p. 291): “… a functionally unitary trait or process should nevertheless not be considered established by a pattern in a single factor analytic research, but must reappear consistently and persistently in independently rotated studies.”

Factor Analysis of a Multiple-Choice Format for Job Satisfaction

1987 ◽  
Vol 61 (3) ◽  
pp. 747-750 ◽  
Author(s):  
Terry Gregson
Keyword(s):  
Job Satisfaction ◽  
Factor Analysis ◽  
Factor Structure ◽  
Analytic Solution ◽  
Multiple Choice ◽  
Job Descriptive Index ◽  
Factor Analytic

This study examined the factor structure of a modified 30-question multiple-choice format for job satisfaction based on the Job Descriptive Index. The five-factor varimax factor analytic solution was the same as that obtained by Smith, Kendall, and Hulin (1969) for the original Job Descriptive Index. The measure of reliability was high. The results indicated that researchers can use a shorter multiple-choice format of job satisfaction based on the Job Descriptive Index without interfering with the dimensionality.

A Factor Analytic Study of the Items in Three Selected Sex-Role Instruments

1980 ◽  
Vol 46 (3_suppl) ◽  
pp. 1119-1126 ◽  
Author(s):  
Judy C. Pearson
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Sex Roles ◽  
Sex Role ◽  
Analytic Study ◽  
Personal Attributes ◽  
Factor Analytic ◽  
Factor Analytic Study ◽  
Midwestern University ◽  
Personal Attributes Questionnaire

A factor analysis of items in the Bern Sex-role Inventory, the Personal Attributes Questionnaire, and Heilbrun's Masculinity and Femininity scales yielded 11 factors. College students ( n = 400) at a large midwestern university completed the items from the three instruments. The solution that emerged suggests that sex roles are multidimensional and that masculinity may be more factorially complex.

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